code: def _get_processing_inputs_with_all_parameters(bucket):
      return [
          ProcessingInput(
              source=f"s3://{bucket}",
              destination="/opt/ml/processing/input/data/",
              input_name="my_dataset",
          ),
          ProcessingInput(
              input_name="s3_input_wo_defaults",
              s3_input=S3Input(
                  s3_uri=f"s3://{bucket}",
                  local_path="/opt/ml/processing/input/s3_input_wo_defaults",
                  s3_data_type="S3Prefix",
              ),
          ),
          ProcessingInput(
              input_name="s3_input",
              s3_input=S3Input(
                  s3_uri=f"s3://{bucket}",
                  local_path="/opt/ml/processing/input/s3_input",
                  s3_data_type="S3Prefix",
                  s3_input_mode="File",
                  s3_data_distribution_type="FullyReplicated",
                  s3_compression_type="None",
              ),
          ),
          ProcessingInput(
              input_name="redshift_dataset_definition",
              app_managed=True,
              dataset_definition=DatasetDefinition(
                  local_path="/opt/ml/processing/input/rdd",
                  data_distribution_type="FullyReplicated",
                  input_mode="File",
                  redshift_dataset_definition=RedshiftDatasetDefinition(
                      cluster_id="integ-test-cluster-prod-us-west-2",
                      database="dev",
                      db_user="awsuser",
                      query_string="SELECT * FROM shoes",
                      cluster_role_arn="arn:aws:iam::037210630505:role/RedshiftClusterRole-prod-us-west-2",
                      output_s3_uri=f"s3://{bucket}/rdd",
                      output_format="CSV",
                      output_compression="None",
                  ),
              ),
          ),
          ProcessingInput(
              input_name="athena_dataset_definition",
              app_managed=True,
              dataset_definition=DatasetDefinition(
                  local_path="/opt/ml/processing/input/add",
                  data_distribution_type="FullyReplicated",
                  input_mode="File",
                  athena_dataset_definition=AthenaDatasetDefinition(
                      catalog="AwsDataCatalog",
                      database="default",
                      work_group="workgroup",
                      query_string='SELECT * FROM "default"."s3_test_table_$STAGE_$REGIONUNDERSCORED";',
                      output_s3_uri=f"s3://{bucket}/add",
                      output_format="JSON",
                      output_compression="GZIP",
                  ),
              ),
          ),
      ]
  
imports: from __future__ import absolute_import
  import os
  import pytest
  from botocore.config import Config
  from sagemaker import image_uris, Session
  from sagemaker.dataset_definition.inputs import DatasetDefinition, RedshiftDatasetDefinition, AthenaDatasetDefinition, S3Input
  from sagemaker.network import NetworkConfig
  from sagemaker.processing import ProcessingInput, ProcessingOutput, ScriptProcessor, Processor, ProcessingJob, FeatureStoreOutput
  from sagemaker.sklearn.processing import SKLearnProcessor
  from tests.integ import DATA_DIR
  from tests.integ.kms_utils import get_or_create_kms_key
label_desc: Use image node_id 16 for calling a global function with example usage: _get_processing_inputs_with_all_parameters(bucket) and returns: list